Search is one of the most misunderstood functionalities in IT. It’s commonly taken for granted, except when it’s missing or broken. If you need proof, just imagine a world with no Google, Bing or other Web search engines. How many websites do you think you’d realistically access? Or, consider for a moment how quickly the Web has grown. Do you think things would have progressed at such a fast pace without being able to instantly access information via search engines?

We use search every single day without really thinking about it. We use it to find locations, books, hotels, apartments, and even homes. Think about it like this: Google Maps, Amazon, Expedia, AirBnB and Craigslist are really search applications at their core. And it’s not just complex applications that we rely on for search, either. Take something as basic as a telephone number; when was the last time you memorized one? I used to have an impeccable memory for telephone numbers, at one point in my life I memorized somewhere around 250 of all friends, family and business—and now I can barely remember my wife’s phone number!

Search changed something as low level as phone numbers. Now when we need one, we simply swipe our smartphones, then Spotlight or some other search shows up and does most of the work for us. It’s quick and easy, and it’s profoundly changing our behavior. But let’s not forget that results are not created equal. A properly tuned search engine can bring back great results -- for example, if a user is looking for a course on Abstract Classes, it can retrieve the best course on this topic. But is it Java Abstract Classes or C# Abstract Classes? This is where personalized searches come in; by creating a profile of users, results can be tailored individually to each user, based on previous searches, viewing habits, ratings, comments in the discussion forums and more.

There are many variables that require consideration beyond matching a query with what your search engine crawled. We run into personalized search each time we use Google. Ever notice that your results often make it seem like Google read your mind and knew exactly what you needed in advance? It only takes typing in a few letters and to get a full (and often accurate) suggestion. It might even feel a little awkward that the search engine can predict your inquiries so accurately. It’s not just Google, either -- this is a path that many companies have taken. These companies know that if they place the right product in front of their users, those users will likely be enticed to purchase. And that’s exactly why companies spend so much time gathering and analyzing data to determine trends and predict purchasing habits.

And with decreasing costs of storage, data transfer and processing going down at bounds and leaps, we're getting much better at gathering all this information for analysis, otherwise known as Big Data (but that’s a topic for another post).

Before we wrap up, consider how far search engines have come; they used to cost millions in licensing fees and they were extremely complex. While there are still some commercial search engines in this category, Apache Solr has worked to change that. Apache Solr is popular, extremely fast, open source, and has a very active community -- and it’s free. If you have the resources to learn it, it can make a difference in the search experience.

Search matters, and it matters to every developer of every application where processed information needs to be retrieved, trends need to be analyzed, or wherever there is simply a "search" function. On the other hand, if there’s no search, it’s highly likely that one may be needed. A bad search experience can frustrate users, reduce engagement and prevent sales. On the other hand, discoverability can increase sales and save money to enterprises. And what better reason could you possibly need?